RI Seminar
Robot Skill Learning: From the Real World to Simulation and Back
Event Location: NSH 1305Bio: Dr. Peter Stone is the David Bruton, Jr. Centennial Professor and Associate Chair of Computer Science, as well as Chair of the Robotics Portfolio Program, at the University of Texas at Austin. In 2013 he was awarded the University of Texas System Regents' Outstanding Teaching Award and in 2014 he was [...]
Robot Skill Learning: From the Real World to Simulation and Back
Peter Stone David Bruton, Jr. Centennial Professor, The University of Texas at Austin Abstract For autonomous robots to operate in the open, dynamically changing world, they will need to be able to learn a robust set of interacting skills. This talk begins by introducing "Overlapping Layered Learning" as a novel hierarchical machine learning paradigm for [...]
Deep Robotic Learning
Sergey Levine Assistant Professor, UC Berkeley Abstract Deep learning methods have provided us with remarkably powerful, flexible, and robust solutions in a wide range of passive perception areas: computer vision, speech recognition, and natural language processing. However, active decision making domains such as robotic control present a number of additional challenges, standard supervised learning methods [...]
Robots for the social good: Identifying and addressing organizational and societal factors in the design and use of robots
Event Location: NSH 1305Bio: I am an Associate Professor of Informatics and Cognitive Science at Indiana University, Bloomington, where I founded and direct the R-House Human-Robot Interaction Lab. My work combines the social studies of computing, focusing particularly on the design, use, and consequences of socially interactive and assistive robots in different social and cultural [...]
Selma Sabanovic: Robots for the social good: Identifying and addressing organizational and societal factors in the design and use of robots
Selma Sabanovic Associate Professor of Informatics and Cognitive Science, Indiana University Bloomington Additional Information Host: Aaron Steinfeld Appointments: Stephanie Matvey Abstract Robots are expected to become ubiquitous in the near future, working alongside and with people in everyday environments to provide various societal benefits. In contrast to this broad ranging social vision for robotics applications, [...]
Robotic Manipulation under clutter and uncertainty with and around people
Abstract Robots manipulate with super-human speed and dexterity on factory floors. But yet they fail even under moderate amounts of clutter or uncertainty. However, human teleoperators perform remarkable acts of manipulation with the same hardware. My research goal is to bridge the gap between what robotic manipulators can do now and what they are capable [...]
Sven Koenig: Progress on Multi-Robot Path Finding
Abstract Teams of robots often have to assign target locations among themselves and then plan collision-free paths to their target locations. Examples include autonomous aircraft towing vehicles and automated warehouse systems. For example, in the near future, autonomous aircraft towing vehicles might tow aircraft all the way from the runways to their gates (and vice [...]
David Held: Robots Learning to Understand Environmental Changes
Abstract Robots today are typically confined to operate in relatively simple, controlled environments. One reason for these limitation is that current methods for robotic perception and control tend to break down when faced with occlusions, viewpoint changes, poor lighting, unmodeled dynamics, and other challenging but common situations that occur when robots are placed in the [...]